Triple

T36371588
Position Surface form Disambiguated ID Type / Status
Subject Lanark E895769 entity
Predicate hasPart P35 FINISHED
Object Book Two
Book Two is one of the four interlinked sections of Alasdair Gray’s novel "Lanark," continuing its experimental blend of realist and dystopian narrative.
E2181390 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Book Two | Statement: [Lanark, hasPart, Book Two]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Book Two
Triple: [Lanark, hasPart, Book Two]
Generated description
Book Two is one of the four interlinked sections of Alasdair Gray’s novel "Lanark," continuing its experimental blend of realist and dystopian narrative.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76e5115588190ad8738860b7bc68b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7baf108a8819089e231babc53f8f7 completed May 3, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b42c7d6c81909b8258e2d1917c24 completed June 22, 2026, 10:16 p.m.
NEDg Description generation batch_6a39b61fe0f8819083be78e09186c2d0 completed June 22, 2026, 10:24 p.m.
NED2 Entity disambiguation (via description) batch_6a39b6bb50a88190ad123d3823585299 completed June 22, 2026, 10:27 p.m.
Created at: May 3, 2026, 4:10 p.m.